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- Clinical reasoning in physical therapy: a…
Clinical reasoning in physical therapy: a concept analysis
- Novice physical therapy students demonstrate limited use of a biopsychosocial model, and mainly drew from a biomedical process of diagnostic reasoning.
- Cognitive errors of premature closure and confirmation bias were evident, and unless de-biasing strategies are purposefully introduced, it’s probable these errors remain present in graduate level practice.
- Individual differences between physical therapy students in their second year of training probably account for more variance in practice than the programs’ content. These differences may still apply after graduation.
BACKGROUND & OBJECTIVE
Understanding how physiotherapists gather and make sense of data obtained from the people they treat is important, because clinical reasoning directly influences treatment and subsequent outcomes. This study gives insight into the reasoning strategies used by physical therapy students in their second year of doctoral training. The study aimed to identify the clinical decisions made, and the clinical reasoning strategies underlying the students’ decisions.
The reliance on diagnosis rather than integrating illness perspectives (particularly the impact of health problems on the person’s life) poses the greatest risk to effective treatment.
This was a qualitative study of students from two universities. One used a “traditional” sequence of clinical exposure woven throughout the program (A), while the other used clinical experiences at the end of training (B).
Eight randomly selected participants took part, four drawn from each program. Each participant had to complete an assessment and treatment plan for a mock patient. Immediately after the session, the researcher interviewed each participant about their clinical reasoning, using “think aloud” protocol and audio-visual prompts. All interviews were audio-recorded, transcribed and analyzed using structural coding (1), following Jones, Jensen & Edwards coding scheme (2). Appropriate steps were taken to enhance credibility/trustworthiness of coding.
All students followed a similar process of interviewing, moving to examinations and tests to identify pathologies, and associated biomechanical or structural links to that pathology. Hypotheses participants generated attended mainly to identifying the patient’s body structures affected by the problem. Those from programme A tended to generate hypotheses related to understanding behavioural characteristics as well as pathology, but it’s notable that none of the participants discussed the impact of pathology on the person’s life, nor the person’s perspective of his/her health problem.
Most students showed a focus on diagnosing the primary pathology as well as movement patterns associated with this, beginning from a biomedical perspective. They also included diagnosing movement impairments, reasoning about procedures, and diagnosing causal factors.
Overall reasoning patterns
Four reasoning patterns were identified, these were (1) following protocol, (2) the hypothetico-deductive process, (3) reasoning about pain, and (4) analysis of patient behavioral patterns. When reasoning about pain, all participants followed a biomedical approach to diagnosis. Three participants used a behavioral approach to reasoning about pain as well as the biomedical one. The authors of the paper comment that even though all the participants collected similar information about the patient, the reasons for obtaining that information, and the way this was interpreted, differed.
Two primary patterns of reasoning error were identified: (1) failing to generate a key hypothesis, and (2) retaining a hypothesis despite contradictory information.
Using the findings for treatment
Participants from the two programs differed in what was prioritised in treatment planning. One programme prioritised education and self-management (program A), while students from the other programme prioritised pain management.
Both groups of students used reflection-in-action and reflection-on-action, and this shaped their clinical decisions. Those using greater reflection-in-action demonstrated greater flexibility to adapt their assessment to what was being found.
Comparing clinical reasoning approaches between participants from two programs based on when students have clinical exposure is probably not the most useful way to draw conclusions about program-level differences, especially in the absence of knowledge about course curricula.
There was no information on how well each participant did in terms of academic abilities, or their previous knowledge, personal experiences and educational backgrounds, making it difficult to use this study to compare the approaches to clinical reasoning development.
I’d add as well that this study was conducted in the US, and training programs elsewhere in the world may differ.
Despite these limitations, this study offers an insight into how emerging physical therapists go about gathering information, organizing that information, and generating treatments. The reliance on diagnosis rather than integrating illness perspectives (particularly the impact of health problems on the person’s life and what they wanted to do) poses the greatest risk to effective treatment. The authors themselves identified that most students drew from a biomedical model, while only two were integrating a biopsychosocial model, and this had the biggest impact on the way students conceptualized pain.
The authors suggest that the different approaches to framing a patient’s problem can both hinder and support effective treatment. It’s evident that physical therapists focus on movement and integrating biomechanical factors thought to contribute to injury. This is problematic when biomechanical contributors to musculoskeletal pain are no longer as strongly supported in musculoskeletal pain research. Clinicians attending to movement at the ‘impairment’ level may also lead them away from focusing on functional assessment, or how people move in the real world.
Of most concern to me is the tendency for all participants in this study to either identify a single hypothesis and fail to shift from this despite evidence to the contrary, or to simply search for information that supported the original hypothesis. Premature closure and confirmation bias are two cognitive errors identified by Croskerry (3,4), and it’s evident that at this stage of training, students did not routinely employ de-biasing strategies.
The critical question is whether graduates continue to demonstrate these errors – and whether de-biasing steps are adopted by more senior professionals.
- Saldana JM. The coding manual for qualitative researchers. London: Sage Publications Ltd; 2009.
- Jones MA, Jensen GM, Edwards I. Clinical reasoning in physiotherapy. In: Higgs J, Jones MA, Loftus S, Christensen N, eds. Clinical reasoning in the health professions. 3rd ed. Amsterdam: Elsevier; 2008:245–256.
- Croskerry, P., Singhal, G., & Mamede, S. (2013). Cognitive debiasing 1: origins of bias and theory of debiasing. BMJ Quality & Safety, 22(Suppl 2), ii58-ii64. doi:10.1136/bmjqs-2012-001712
- Croskerry, P., Singhal, G., & Mamede, S. (2013). Cognitive debiasing 2: impediments to and strategies for change. BMJ Quality & Safety, 22(Suppl 2), ii65-ii72. doi:10.1136/bmjqs-2012-001713